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Then, by introducing kernel\u2010free tricks, two multiview classifiers are proposed, called <jats:italic>C<\/jats:italic>\u2010multiview kernel\u2010free nonlinear support vector machine (<jats:italic>C<\/jats:italic>\u2010MKNSVM) and its <jats:italic>\u03bd<\/jats:italic>\u2010version, namely, <jats:italic>\u03bd<\/jats:italic>\u2010MKNSVM. They try to find a quadratic hypersurface under each view to classify the sample points and employ a consistency constraint to fuse the sample points from two views. Both the primal and dual problems of <jats:italic>C<\/jats:italic>\u2010MKNSVM and <jats:italic>\u03bd<\/jats:italic>\u2010MKNSVM do not involve kernel functions; thus, they are allowed to be solved directly. In addition, the relationship of solutions between the primal and dual problems is discussed in each classifier. 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